Minimum complexity integrated photonic architecture for delay-based reservoir computing.

Reservoir computing is an analog bio-inspired computation scheme for efficiently processing time-dependent signals, the photonic implementations of which promise a combination of massive parallel information processing, low power consumption, and high-speed operation. However, most of these implementations, especially for the case of time-delay reservoir computing, require extensive multi-dimensional parameter optimization to find the optimal combination of parameters for a given task. We propose a novel, largely passive integrated photonic TDRC scheme based on an asymmetric Mach-Zehnder interferometer in a self-feedback configuration, where the nonlinearity is provided by the photodetector, and with only one tunable parameter in the form of a phase shifting element that, as a result of our configuration, allows also to tune the feedback strength, consequently tuning the memory capacity in a lossless manner. Through numerical simulations, we show that the proposed scheme achieves good performance -when compared to other integrated photonic architectures- on the temporal bitwise XOR task and various time series prediction tasks, while greatly reducing hardware and operational complexity.

Density-dependent private benefit leads to bacterial mutualism.

Microorganisms produce and secrete materials that are beneficial for themselves and their neighbors. We modeled the situation when cells can produce different costly secretions which increase the carrying capacity of the population. Strains that lose the function of producing one or more secretions avoid the cost of production and can exhaust the producers. However, secreting substances provides a private benefit for the producers in a density-dependent way. We developed a model to examine the outcome of the selection among different types of producer strains from the nonproducer strain to the partial producers, to the full producer strain. We were interested in circumstances under which selection maintains partners that produce complementary secreted materials thus forming an interdependent mutualistic interaction. We show that interdependent mutualism is selected under a broad range of conditions if private benefit decreases with density. Selection frequently causes the coexistence of more and less generalist cooperative strains, thus cooperation and exploitation co-occur. Interdependent mutualism is evolved under more specific circumstances if private benefit increases with density and these general observations are valid in a well-mixed and a structured deme model. We show that the applied population structure allows the invasion of rare cooperators and supports cooperation in general.

Who uses apps in health promotion? A target group analysis of leaders.

User characteristics should be considered when designing features for e-health or m-health applications, as the developed solution should aim to support this specific target group. This study explores the effect of user characteristics (personality, health state, stress/recovery state, leadership behavior) on the interest and likelihood of using an app for health promotion activities at the workplace. Leaders are a key factor for the success of workplace health promotion; therefore, the target group of this study are leaders. The data of 412 leaders were collected in an online study. Hierarchical multiple linear regression analyses were conducted for four outcome criteria ("personal health," "contacting," "leadership feedback" and "corporate key figures"). The findings showed that neuroticism, physical health and health-promoting leadership were important predictors for using an app for monitoring personal health and getting in social contact about health issues. The stress/recovery state was significantly related to the feature of getting in social contact.

Enhancing Resources at the Workplace with Health-Promoting Leadership.

Leaders engaging in health-promoting leadership can influence their employees' health directly by showing health awareness or indirectly by changing working conditions. With health-promoting leadership, leaders are able to support a healthy working environment by providing resource-oriented working conditions for their employees to support their health. Changing working conditions in a health-supportive way can prevent possible negative consequences from critical working conditions (e.g., burnout risk). The present study examined the relationship between health-promoting leadership and the employees' resources, stress and burnout. To analyze our proposed model, structural equation modelling was conducted in two samples. The resulting model from the first sample of 228 Austrian workers was cross-validated and could be verified with the second sample (N = 263 Austrian workers). The results supported a model in which health-promoting leadership has a strong direct effect on the employees' resources and an indirect effect on stress and burnout, which was mediated by resources. The results indicate that health-promoting leadership describes the leaders' capability and dedication creating the right working conditions for their employees by increasing the employees' resources at the workplace. This in turn minimizes the risk of experiencing burnout.

The Buffering Effect of Workplace Resources on the Relationship between the Areas of Worklife and Burnout.

Background: Workplace resources are found to play a major role in the stress-strain relationship. However, usually different types of resources are investigated, whereas investigating different facets of stress ("stressors") receive less attention in research about the relationship between stress, strain and resources. Based upon recent research, we expected that workplace resources moderate the relationship between stressors (operationalized with the areas of worklife) and long-term strain (operationalized with three dimensions of burnout) in the sense that workplace resources buffer the negative effects of stressors on strain. Method: Hypotheses were tested in a longitudinal sample of 141 Austrian workers, who participated two times in an online study over a period of 6 months. Hierarchical multiple regression analysis was used to test the proposed relationships. Results: The results imply that workload and reward seem to be the most important predictors for burnout. Workload is important for emotional exhaustion, whereas reward is important for cynicism. Value-fit at the workplace plays a significant role for cynicism, but only if resources at the workplace are high. Further moderating effects of resources were found for the outcome personal accomplishment. More specifically, results indicate that having high resources in a high workload environment increases personal accomplishment after a time interval of 6 months. In addition, employees experiencing high levels of control but low workplace resources show less personal accomplishment. Conclusion: Despite the limiting aspects of the relatively short period of time we can see that resources can buffer workload effects. This should be taken into consideration when doing risk assessments in practice as work design should focus on resources even more when high workload can be found.

Using smartphone-based applications (apps) in workplace health promotion: The opinion of German and Austrian leaders.

Reaching the actual target group for a web-based health promotion project turns out to be a difficult task. In this article, individual and organizational factors which can influence the decision of using apps in workplace health promotion are analyzed. Furthermore, we analyzed the opinion about feedback possibilities of apps in workplace health promotion. A study with 438 leaders was conducted, as leaders can be seen as a key factor in the success of health promotion projects. The results showed that younger leaders and leaders with a more positive attitude toward workplace health promotion are more likely to use an app. Furthermore, leaders with a positive attitude are more interested in expert-feedback than in instant feedback received from an app.